A Novel 12-Lead Electrocardiographic System for Home Use: Development and Usability Testing

An augmented reality-based method to assess precordial electrocardiogram leads: a feasibility trial

Aims

It has been demonstrated that several cardiac pathologies, including myocardial ischaemia, can be detected using smartwatch electrocardiograms (ECGs). Correct placement of bipolar chest leads remains a major challenge in the outpatient population.

Methods and results

In this feasibility trial, we propose an augmented reality-based smartphone app that guides the user to place the smartwatch in predefined positions on the chest using the front camera of a smartphone. A machine-learning model using MobileNet_v2 as the backbone was trained to detect the bipolar lead positions V1-V6 and visually project them onto the user's chest. Following the smartwatch recordings, a conventional 10 s, 12-lead ECG was recorded for comparison purposes. All 50 patients participating in the study were able to conduct a 9-lead smartwatch ECG using the app and assistance from the study team. Twelve patients were able to record all the limb and chest leads using the app without additional support. Bipolar chest leads recorded with smartwatch ECGs were assigned to standard unipolar Wilson leads by blinded cardiologists based on visual characteristics. In every lead, at least 86% of the ECGs were assigned correctly, indicating the remarkable similarity of the smartwatch to standard ECG recordings.

Conclusion

We have introduced an augmented reality-based method to independently record multichannel smartwatch ECGs in an outpatient setting.

Feasibility of patch-type wireless 12-lead electrocardiogram in laypersons

Various efforts have been made to diagnose acute cardiovascular diseases (CVDs) early in patients. However, the sole option currently is symptom education. It may be possible for the patient to obtain an early 12-lead electrocardiogram (ECG) before the first medical contact (FMC), which could decrease the physical contact between patients and medical staff. Thus, we aimed to verify whether laypersons can obtain a 12-lead ECG in an off-site setting for clinical treatment and diagnosis using a patch-type wireless 12-lead ECG (PWECG). Participants who were ≥ 19 years old and under outpatient cardiology treatment were enrolled in this simulation-based one-arm interventional study. We confirmed that participants, regardless of age and education level, can use the PWECG on their own. The median age of the participants was 59 years (interquartile range [IQR] = 56-62 years), and the median duration to obtain a 12-lead ECG result was 179 s (IQR = 148-221 s). With appropriate education and guidance, it is possible for a layperson to obtain a 12-lead ECG, minimizing the contact with a healthcare provider. These results can be used subsequently for treatment.

Signal Quality Analysis for Long-Term ECG Monitoring Using a Health Patch in Cardiac Patients

Cardiovascular diseases (CVD) represent a serious health problem worldwide, of which atrial fibrillation (AF) is one of the most common conditions. Early and timely diagnosis of CVD is essential for successful treatment. When implemented in the healthcare system this can ease the existing socio-economic burden on health institutions and government. Therefore, developing technologies and tools to diagnose CVD in a timely way and detect AF is an important research topic. ECG monitoring patches allowing ambulatory patient monitoring over several days represent a novel technology, while we witness a significant proliferation of ECG monitoring patches on the market and in the research labs, their performance over a long period of time is not fully characterized. This paper analyzes the signal quality of ECG signals obtained using a single-lead ECG patch featuring self-adhesive dry electrode technology collected from six cardiac patients for 5 days. In particular, we provide insights into signal quality degradation over time, while changes in the average ECG quality per day were present, these changes were not statistically significant. It was observed that the quality was higher during the nights, confirming the link with motion artifacts. These results can improve CVD diagnosis and AF detection in real-world scenarios.

Isoflurane Preconditioning May Attenuate Cardiomyocyte Injury Induced by Hypoxia/Reoxygenation Possibly by Regulating miR-363-3p

This study attempted to explore whether miR-363-3p play a role in the isoflurane (ISO)-mediated protective effect of cardiomyocyte injury induced by hypoxia/reoxygenation (H/R). A myocardial cell injury model was established, and the different preconditioning ISO concentrations were screened and determined. The miR-363-3p level was detected by RT-qPCR. The effects of miR-363-3p on proliferation and apoptosis of H9c2 cells were detected by CCK-8 assay and flow cytometry. Myocardial injury indexes were determined by enzyme-linked immunosorbent assay (ELISA). The interaction of miR-363-3p with the 3'-UTR of the KLF2 gene was confirmed by luciferase reporter gene assay. ISO pretreatment can reduce the up-regulation of miR-363-3p after H/R injury. ISO pretreatment reduces the inhibition of cell viability and the promotion of cell apoptosis induced by H/R stimuli, while the overexpression of miR-363-3p counteracts the protective effect of ISO pretreatment. Meanwhile, ISO pretreatment also reduced the level of markers of H/R-induced myocardial injury. Moreover, luciferase reporter analysis showed that KLF2 was the downstream target gene of miR-363-3p. ISO pretreatment may alleviate H/R-induced cardiomyocyte injury by regulating miR-363-3p.

Peak Detection and HRV Feature Evaluation on ECG and PPG Signals

Heart Rate Variability (HRV) evaluates the autonomic nervous system regulation and can be used as a monitoring tool in conditions such as cardiovascular diseases, neuropathies and sleep staging. It can be extracted from the electrocardiogram (ECG) and the photoplethysmogram (PPG) signals. Typically, the HRV is obtained from the ECG processing. Being the PPG sensor widely used in clinical setups for physiological parameters monitoring such as blood oxygenation and ventilatory rate, the question arises regarding the PPG adequacy for HRV extraction. There is not a consensus regarding the PPG being able to replace the ECG in the HRV estimation. This work aims to be a contribution to this research area by comparing the HRV estimation obtained from simultaneously acquired ECG and PPG signals from forty subjects. A peak detection method is herein introduced based on the Hilbert transform: Hilbert Double Envelope Method (HDEM). Two other peak detector methods were also evaluated: Pan-Tompkins and Wavelet-based. HRV parameters for time, frequency and the non-linear domain were calculated for each algorithm and the Pearson correlation, T-test and RMSE were evaluated. The HDEM algorithm showed the best overall results with a sensitivity of 99.07% and 99.45% for the ECG and the PPG signals, respectively. For this algorithm, a high correlation and no significant differences were found between HRV features and the gold standard, for the ECG and PPG signals. The results show that the PPG is a suitable alternative to the ECG for HRV feature extraction.

A community effort to assess and improve computerized interpretation of 12-lead resting electrocardiogram

Computerized interpretation of electrocardiogram plays an important role in daily cardiovascular healthcare. However, inaccurate interpretations lead to misdiagnoses and delay proper treatments. In this work, we built a high-quality Chinese 12-lead resting electrocardiogram dataset with 15,357 records, and called for a community effort to improve the performances of CIE through the China ECG AI Contest 2019. This dataset covers most types of ECG interpretations, including the normal type, 8 common abnormal types, and the other type which includes both uncommon abnormal and noise signals. Based on the Contest, we systematically assessed and analyzed a set of top-performing methods, most of which are deep neural networks, with both their commonalities and characteristics. This study establishes the benchmarks for computerized interpretation of 12-lead resting electrocardiogram and provides insights for the development of new methods.

Graphical Abstract

Twelve-Lead Electrocardiogram Acquisition With a Patchy-Type Wireless Device in Ambulance Transport: Simulation-Based Randomized Controlled Trial

Background

Cardiovascular disease is the leading cause of death worldwide. Early recognition, diagnosis, and reperfusion are the key elements of treatment for ST-segment elevation myocardial infarction. The absence of a prehospital 12-lead electrocardiogram (P12ECG) can cause definitive treatment delay and repeated transfer. Although guidelines highly recommend the measurement and transmission of P12ECG data, P12ECG use has not been widely established.

Objective

The aim of this study was to verify the time-efficiency and feasibility of the use of a patchy-type 12-lead ECG measuring and transmitting device (P-ECG) by an emergency medical technician (EMT) in an ambulance during patient transport.

Methods

This was a simulation-based prospective randomized crossover-controlled study that included EMTs. The participants were randomly assigned to one of two groups. Group A began the experiment with a conventional 12-lead ECG (C-ECG) device and then switched to the intervention device (P-ECG), whereas group B began the experiment with the P-ECG and then switched to the C-ECG. All simulations were performed inside an ambulance driving at 30 km/h. The time interval was measured from the beginning of ECG application to completion of sending the results. After the simulation, participants were administered the System Usability Scale questionnaire about usability of the P-ECG.

Results

A total of 18 EMTs were recruited for this study with a median age of 35 years. The overall interval time for the C-ECG was 254 seconds (IQR 247-270), whereas the overall interval time for the P-ECG was 130 seconds (IQR 112-150), with a significant difference (P<.001). Significant differences between the C-ECG and P-ECG were identified at all time intervals, in which the P-ECG device was significantly faster in all intervals, except for the preparation interval in which the C-ECG was faster (P=.03).

Conclusions

Performance of 12-lead ECG examination and transmission of the results using P-ECG are faster than those of C-ECG during ambulance transport. With the additional time afforded, EMTs can provide more care to patients and transport patients more rapidly, which may help reduce the symptoms-to-balloon time for patients with acute coronary syndrome.

Trial Registration

ClinicalTrials.gov NCT04114760; https://www.clinicaltrials.gov/ct2/show/NCT04114760

Current Use and Future Needs of Noninvasive Ambulatory Electrocardiogram Monitoring

Remarkable progress has been seen in monitoring systems using noninvasive ambulatory electrocardiograms (ECGs). In the Holter ECG system, 12-channel formats have been utilized as diagnostic tools, particularly for the detection of transient or silent myocardial ischemia and dynamic electrical disorders. In patients diagnosed with cryptogenic stroke, despite negative results on standard ECG tests, continuous ambulatory ECG monitoring for up to 30 days has been shown to increase the detection rate of transient atrial fibrillation. At present, a waterproof Holter ECG system is available. Recently, continuous late potential measurements using the time domain method and frequency domain T-wave alternans using the spectral analysis method for 24 hours have been applied to the Holter ECG and developed as novel risk stratification markers. Wearable ECG monitors that are built into belts, vests, wristbands, adhesive patches, and mobile smartphones have been used as fitness products for athletes and healthcare products for the general population. In the future, such devices may be used as remote monitoring tools for the detection of arrhythmias.

Use of a Smart Watch for Early Detection of Paroxysmal Atrial Fibrillation: Validation Study

Background

Wearable devices with photoplethysmography (PPG) technology can be useful for detecting paroxysmal atrial fibrillation (AF), which often goes uncaptured despite being a leading cause of stroke.

Objective

This study is the first part of a 2-phase study that aimed at developing a method for immediate detection of paroxysmal AF using PPG-integrated wearable devices. In this study, the diagnostic performance of 2 major smart watches, Apple Watch Series 3 and Fitbit (FBT) Charge HR Wireless Activity Wristband, each equipped with a PPG sensor, was compared, and the pulse rate data outputted from those devices were analyzed for precision and accuracy in reference to the heart rate data from electrocardiography (ECG) during AF.

Methods

A total of 40 subjects from patients who underwent cardiac surgery at a single center between September 2017 and March 2018 were monitored for postoperative AF using telemetric ECG and PPG devices. AF was diagnosed using a 12-lead ECG by qualified physicians. Each subject was given a pair of smart watches, Apple Watch and FBT, for simultaneous pulse rate monitoring. The heart rate of all subjects was also recorded on the telemetry system. Time series pulse rate trends and heart rate trends were created and analyzed for trend pattern similarities. Those trend data were then used to determine the accuracy of PPG-based pulse rate measurements in reference to ECG-based heart rate measurements during AF.

Results

Of the 20 AF events in group FBT, 6 (30%) showed a moderate or higher correlation (cross-correlation function>0.40) between pulse rate trend patterns and heart rate trend patterns. Of the 16 AF events in group Apple Watch (workout [W] mode), 12 (75%) showed a moderate or higher correlation between the 2 trend patterns. Linear regression analyses also showed a significant correlation between the pulse rates and the heart rates during AF in the subjects with Apple Watch. This correlation was not observed with FBT. The regression formula for Apple Watch W mode and FBT was X=14.203 + 0.841Y and X=58.225 + 0.228Y, respectively (where X denotes the mean of all average pulse rates during AF and Y denotes the mean of all corresponding average heart rates during AF), and the coefficient of determination (R²) was 0.685 and 0.057, respectively (P<.001 and .29, respectively).

Conclusions

In this validation study, the detection precision of AF and measurement accuracy during AF were both better with Apple Watch W mode than with FBT.

Design Perceptions for 3D Printed Accessories of Digital Devices and Consumer-Based Brand Equity

Drawn on means-end theory and relationalism, this study investigates the impact of 3D printed branded accessories' design perception on consumer-based brand equity (CBBE). In addition, how experiential value mediates the relationship between product design perception and CBBE. Based on a random sampling approach, the present study collected 535 3D printed branded accessories users' responses through social media (WeChat). The data were analyzed through partial least squares, structural equation modeling (PLS-SEM) approach, smart PLS-3. The results reveal that two dimensions of design perception (functional and kinesthetic) have a significant impact on CBBE. However, design perception (visual) has failed to impact significantly on CBBE. The experiential value significantly mediates the relationship between all dimensions (visual, functional, and kinesthetic) of design perception and CBBE. This study concludes that experiential value/user experience is an inevitable mediator between product design perception and CBBE. The implication and limitations of this study are discussed in the last section of this study.

Accuracy of mHealth Devices for Atrial Fibrillation Screening: Systematic Review

BACKGROUND

Mobile health (mHealth) devices can be used for the diagnosis of atrial fibrillation. Early diagnosis allows better treatment and prevention of secondary diseases like stroke. Although there are many different mHealth devices to screen for atrial fibrillation, their accuracy varies due to different technological approaches.

OBJECTIVE

We aimed to systematically review available studies that assessed the accuracy of mHealth devices in screening for atrial fibrillation. The goal of this review was to provide a comprehensive overview of available technologies, specific characteristics, and accuracy of all relevant studies.

METHODS

PubMed and Web of Science databases were searched from January 2014 until January 2019. Our systematic review was performed according to the Preferred Reporting Items for Systematic Review and Meta-Analyses. We restricted the search by year of publication, language, noninvasive methods, and focus on diagnosis of atrial fibrillation. Articles not including information about the accuracy of devices were excluded.

RESULTS

We found 467 relevant studies. After removing duplicates and excluding ineligible records, 22 studies were included. The accuracy of mHealth devices varied among different technologies, their application settings, and study populations. We described and summarized the eligible studies.

CONCLUSIONS

Our systematic review identifies different technologies for screening for atrial fibrillation with mHealth devices. A specific technology's suitability depends on the underlying form of atrial fibrillation to be diagnosed. With the suitable use of mHealth, early diagnosis and treatment of atrial fibrillation are possible. Successful application of mHealth technologies could contribute to significantly reducing the cost of illness of atrial fibrillation.

Risk Evaluation of Azithromycin-Induced QT Prolongation in Real-World Practice

Background

Azithromycin exposure has been reported to increase the risk of QT prolongation and cardiovascular death. However, findings on the association between azithromycin and cardiovascular death are controversial, and azithromycin is still used in actual practice. Additionally, quantitative assessments of risk have not been performed, including the risk of QT prolongation when patients are exposed to azithromycin in a real-world clinical setting. Therefore, in this study, we aimed to evaluate the risk of exposure to azithromycin on QT prolongation in a real-world clinical setting using a 21-year medical history database of a tertiary medical institution.

Methods

We analyzed the electrocardiogram results and relevant electronic health records of 402,607 subjects in a tertiary teaching hospital in Korea from 1996 to 2015. To evaluate the risk of QT prolongation of azithromycin, we conducted a case-control analysis using amoxicillin for comparison. Multiple logistic regression analysis was performed to correct for age, sex, accompanying drugs, and disease.

Results

The odds ratio (OR) for QT prolongation (QTc>450 ms in male and >460 ms in female) on azithromycin exposure was 1.40 (95% confidence interval [CI], 1.23-1.59), and the OR for severe QT prolongation (QTc>500 ms) was 1.43 (95% CI, 1.13-1.82). On the other hand, the ORs on exposure to amoxicillin were 1.06 (95% CI, 0.97-1.15) and 0.88 (95% CI, 0.70-1.09). In a subgroup analysis, the risk of QT prolongation in patients aged between 60 and 80 years was significantly higher when they are exposed to azithromycin.

Conclusions

The risk of QT prolongation was increased when patients, particularly the elderly aged 60-79 years, were exposed to azithromycin. Therefore, clinicians should pay exercise caution using azithromycin or consider using other antibiotics, such as amoxicillin, instead of azithromycin.